How InMoment Assists with Regulatory Compliance

The challenges involved in regulatory compliance vary greatly between industries, countries, and companies. But many compliance tools lack flexibility or are missing key technologies for parsing complex structures in legal, medical and financial documents. That’s where InMoment comes in.

Leverage InMoment to Lower Your Regulatory Compliance Costs and Risks

InMoment helps you tackle compliance challenges involving text data through “semi-custom” solutions. We combine semi-structured data parsing, natural language processing (NLP), and machine learning with other features and technology suited to your specific problems. By working from our existing infrastructure through a staged Proof of Concept, we reduce your initial investment and deliver tangible results more quickly. 

We don’t “solve” or automate your entire industry. Instead, we help you improve existing compliance processes and scale your compliance teams more easily, resulting in lower costs and reduced risk across your organization.

Your Regulatory Compliance Technology Toolkit

Curious about the tech InMoment provides that will help you get the job done? Here’s an overview of your toolkit:

Natural Language Processing Features

  • Sentiment Analysis: Combine natural language processing (NLP) and machine learning techniques to assign weighted sentiment scores to the entities, topics, themes and categories within a sentence or phrase.
  • Theme Analysis: Use natural language processing (NLP) to break down sentences into n-grams and noun phrases and then evaluate the themes and facets within.
  • Entity Recognition:  Identify people, places, and things within a piece of text.
  • Categorization: Categorize customer reviews, support tickets, or any other type of text document into groups based on their contents.
  • Intention Extraction: Determine the expressed intent of customers and reviewers.
  • Summarization: Extract the most relevant sentences from each document so you can quickly understand the main ideas without spending valuable time reading the whole document.

Semi-Structured Data Parsing: A powerful tool for identifying and extracting text data from PDFs, .docx files and other “semi-structured” documents while understanding the structures and relationships of each element.

Machine Learning: Custom machine learning “micromodels” to tackle unique challenges in your data, such as entity recognition on ambiguous company names or classifying news articles into pre-defined topic lists.

Add-ons and Integrations: 

  • ​​Low-level NLP configuration
  • Custom user interfaces
  • Specific technology integrations
  • Feedback loops for model training
  • User and project management tools
  • Database/warehouse hookups
  • Upload wizards and connectors
  • …. And more

InMoment for Regulatory Compliance in Action: A Quick Case Study

InMoment has helped brands across healthcare, biotechnology, pharmaceuticals, financial services, and more, but today we will share a financial services case study.

An Australian financial services firm needed help ensuring their compliance with federal disclosure mandates across hundreds of Statement of Advice (SoA) documents. Before, the firm’s auditors manually reviewed a subset, but this process was slow and unreliable.

InMoment focused on improving the firm’s existing audit process. First, we trained our semi-structured data parser to understand the underlying structure of SoAs. Then we configured our NLP to identify, extract and analyze entities within each section. Finally, we built a connector to structure and export this data into an easy-to-scan spreadsheet.

“InMoment’s solution for financial services disclosure compliance identifies, analyzes and structures key data from Statement of Advice documents for internal review.”

This solution substantially reduces the firm’s noncompliance risk by empowering regulatory compliance auditors to review hundreds of documents in minutes. Now they can quickly and reliably spot missing disclosures, suspicious recommendations, and other areas where advisors may not be working in their clients’ best interests.

To learn more about how InMoment can help revolutionize your approach to regulatory compliance, check out our dedicated website here.

Natural Language Processing 101: Three Tips for Optimising Your Text Analytics Software

When it comes to experience programs, text analytics software has been revolutionising data interpretation since the capability arrived on the scene. I’m Siobhan May Jones, one of InMoment’s Customer Success Directors, and over my career, I’ve seen this transition up close.

One of my first jobs whilst studying at university was manually coding thousands of verbatims about pet food. While this was great financially because I got paid by the hour, it wasn’t a good use of time by today’s standards. Over the next five years, I worked in the market research industry and found that too many tasks are manual process-rich, as well as subject to human error. It has taken years of discipline to rewire my brain from manual work to working with experts and tools to achieve the right goal. 

Let me give you an example—let’s say you need to understand what customers are saying about your employees each month. Your goal is to track which employees you need to support, and which ones need to be celebrated. 

You have two options:

 1) Download a raw extract of the verbatim and read through it month by month, gain an understanding of what customers are saying, then talk to the team about it. 

 2) Use natural language processing tools to visualise where and why these comments are showing excellence or areas requiring improvement.

It’s not really a choice between these two options, as the first scenario has you spending hours clicking buttons and cleaning or filtering data, while the second forces you to make an action plan. 

So how can you optimise your text analytics software and, ultimately, strengthen your customer experience (CX) program? I have three tips for you:

Tip #1: Confirm You’re Using the Latest and Greatest Software 

Before taking any action with text analytics, we recommend chatting with experts in your field to make sure you have the latest tools, processes, software, and overall capability. Your text analytics software should have these four features:


A solution that supports all of the countries and languages your customers work and buy in—at an acceptable level of quality and price.


Your text analytics solution must be able to surface important trends and patterns based on individual comments and the sentiments behind them.


You need a layer of sophisticated analytics that can add tags and themes on a granular level, uncover sentiment, assign categories, identify intent, spot legal issues, and pick up on possible customer churn.


A solution with real-time analysis, reporting and action. This is specifically relevant when considering translations for global companies.

If your text analytics software is missing any of these features, you’ll be starting at a disadvantage. Here at InMoment, we’re constantly innovating based on clients’ specific needs to ensure we’re helping reduce processes and increase action. 

Tip #2: Keep Your Goal Front of Mind When Processing Customer Feedback

When you designed your customer experience program, you no doubt started with a goal in mind. And when it comes to processing thousands of unstructured pieces of customer feedback, it can be easy to lose sight of the original goal. 

We recommend being honest and clear with your team (and yourself) about what your primary goal is, then using the right approach for that goal. Are you looking to add qualitative information to bring life to your metrics, trying to understand what makes customers angry or frustrated, or are you looking to track a recent frontline training initiative and see if customers noticed enough to talk about it? 

Alternatively, are you looking to set up alerts based on topics (regardless of the many possible typos)? Text analytics is a powerful tool that will help you with any of the above goals.  

Tip #3: Be On The Lookout For New Updates

When it comes to text analytics software, there will always be new updates, new features, and new opportunities. We recommend adding a biannual calendar note to yourself to proactively identify how text analytics software is changing over time. By being open to change and by constantly onboarding new features, you have a real opportunity to stay ahead of the competition by keeping focus on continuous Experience Improvement (XI). 

For more information on text analytics, check out this eBook!

Change Region

Selecting a different region will change the language and content of

North America
United States/Canada (English)
DACH (Deutsch) United Kingdom (English) France (français) Italy (Italian)
Asia Pacific
Australia (English) New Zealand (English) Singapore (English)